1. departure delay by city

# read in dataset
library(plotly)

## Loading required package: ggplot2

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
## 
##     layout

packageVersion('plotly')

## [1] '4.8.0'

library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

df <- read.csv("C:/Users/ziwan/Desktop/2018 Fall Courses/BST 260/Project/201701.csv")

# calculate mean departure delay minutes by city
city_delay <- df %>%
  group_by(ORIGIN_CITY_NAME) %>%
  summarize(mean_delay = mean(DEP_DELAY_NEW, na.rm = TRUE))

library(splitstackshape)
city_delay <- cSplit(city_delay, "ORIGIN_CITY_NAME", sep=",")

city_delay <- city_delay %>% mutate(name = ORIGIN_CITY_NAME_1)

# add the coordination of cities
coordinate <- read.csv('https://raw.githubusercontent.com/plotly/datasets/master/2014_us_cities.csv')


city_delay <- city_delay %>% mutate(name = trimws(as.character(name)))

coordinate <- coordinate %>% mutate(name = trimws(as.character(name)))

merged_city_delay <- left_join(city_delay,coordinate, by='name')

merged_city_delay <- merged_city_delay %>% 
  group_by(name) %>%
  summarize(mean_delay = mean(mean_delay, na.rm = TRUE), lat = mean(lat), lon = mean(lon))

# draw the plot by cities
merged_city_delay$q <- with(merged_city_delay, cut(mean_delay, quantile(mean_delay)))
levels(merged_city_delay$q) <- paste(c("1st", "2nd", "3rd", "4th", "5th"), "Quantile")
merged_city_delay$q <- as.ordered((merged_city_delay$q))


g <- list(
  scope = 'usa',
  projection = list(type = 'albers usa'),
  showland = TRUE,
  landcolor = toRGB("gray85"),
  subunitwidth = 1,
  countrywidth = 1,
  subunitcolor = toRGB("white"),
  countrycolor = toRGB("white")
)


p <- plot_geo(merged_city_delay, locationmode = 'USA-states', sizes = c(1, 250)) %>%
  add_markers(
    x = ~lon, y = ~lat, size = ~mean_delay, color = ~q, hoverinfo = "text",
    text = ~paste(merged_city_delay$name, "<br />", merged_city_delay$mean_delay, "minutes")
  ) %>%
  layout(title = '2017 January average departure delay (minutes) by city', geo = g)




p

## Warning: Ignoring 92 observations

## Warning: `line.width` does not currently support multiple values.

## Warning: `line.width` does not currently support multiple values.

## Warning: `line.width` does not currently support multiple values.

## Warning: `line.width` does not currently support multiple values.

2. arrival delay by city

# calculate mean departure delay minutes by city
city_delay <- df %>%
  group_by(DEST_CITY_NAME) %>%
  summarize(mean_delay = mean(ARR_DELAY_NEW, na.rm = TRUE))

library(splitstackshape)
city_delay <- cSplit(city_delay, "DEST_CITY_NAME", sep=",")

city_delay <- city_delay %>% mutate(name = DEST_CITY_NAME_1)

# add the coordination of cities
coordinate <- read.csv('https://raw.githubusercontent.com/plotly/datasets/master/2014_us_cities.csv')


city_delay <- city_delay %>% mutate(name = trimws(as.character(name)))

coordinate <- coordinate %>% mutate(name = trimws(as.character(name)))

merged_city_delay <- left_join(city_delay,coordinate, by='name')

merged_city_delay <- merged_city_delay %>% 
  group_by(name) %>%
  summarize(mean_delay = mean(mean_delay, na.rm = TRUE), lat = mean(lat), lon = mean(lon))

# draw the plot by cities
merged_city_delay$q <- with(merged_city_delay, cut(mean_delay, quantile(mean_delay)))
levels(merged_city_delay$q) <- paste(c("1st", "2nd", "3rd", "4th", "5th"), "Quantile")
merged_city_delay$q <- as.ordered((merged_city_delay$q))


g <- list(
  scope = 'usa',
  projection = list(type = 'albers usa'),
  showland = TRUE,
  landcolor = toRGB("gray85"),
  subunitwidth = 1,
  countrywidth = 1,
  subunitcolor = toRGB("white"),
  countrycolor = toRGB("white")
)


p <- plot_geo(merged_city_delay, locationmode = 'USA-states', sizes = c(1, 250)) %>%
  add_markers(
    x = ~lon, y = ~lat, size = ~mean_delay, color = ~q, hoverinfo = "text",
    text = ~paste(merged_city_delay$name, "<br />", merged_city_delay$mean_delay, "minutes")
  ) %>%
  layout(title = '2017 January average arrival delay (minutes) by city', geo = g)



p

## Warning: Ignoring 91 observations

## Warning: `line.width` does not currently support multiple values.

## Warning: `line.width` does not currently support multiple values.

## Warning: `line.width` does not currently support multiple values.

## Warning: `line.width` does not currently support multiple values.